Clinical praxis for assessment of dry weight in <scp>S</scp>weden and <scp>D</scp>enmark: A mixed‐methods study
Bibliographic record
Abstract
Overhydration is an independent predictor of mortality in hemodialysis (HD) patients. More than 30% of HD patients are overhydrated, motivating the development of new methods for assessing hydration status. This study surveyed clinical praxis and local guidelines for dry weight (DW) assessment in Swedish and Danish HD units, and examined if differences in routines and utilization of bioimpedance spectroscopy (BIS) and other assistive technology affected frequency of DW adjustments and blood pressure (BP) levels. Cross-sectional information on praxis, guidelines and routines, plus treatment-related data from 99 stratified patients were collected. Qualitative data were analyzed with content analysis and interpreted in convergence with statistical analysis of quantitative data in a mixed-methods design. Local guidelines concerning DW existed in 54% of the units. A BIS device was present in 52%, but only half of those units used it regularly, and no correlations to frequency of DW adjustments or BP were found. HD nurses were authorized to adjust DW in 60% of the units; in these units, the frequency of DW adjustments was 1.6 times higher and systolic BP pre-HD 8 mmHg lower. There is a wide variation in routines for DW determination, and there are indications that authorization of HD nurses to adjust DW may improve DW assessment. BIS is sparsely used; its implementation may have been delayed by uncertainty over how to manage the device and interpret measurements. Hence, better methods and guidelines for assessing DW and using BIS need to be developed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".